{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "w1UKrOIrwl0T"
   },
   "source": [
    "# **Feature Extraction**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6L4EIksc10E3"
   },
   "source": [
    "![image.png](data:image/png;base64,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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "edLh1cKp12zf"
   },
   "source": [
    "- Load libreries\n",
    "- Feature extraction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "12S4m38Q4Cw_"
   },
   "source": [
    "## Load Libreries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 6943,
     "status": "ok",
     "timestamp": 1742519811253,
     "user": {
      "displayName": "David Morantes Duarte",
      "userId": "14011841075109377578"
     },
     "user_tz": 300
    },
    "id": "OxwpTxqOwrLj",
    "outputId": "f53e6c49-e7df-48a8-daea-a7787df50302"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: mahotas in /usr/local/lib/python3.11/dist-packages (1.4.18)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from mahotas) (2.0.2)\n"
     ]
    }
   ],
   "source": [
    "!pip install mahotas\n",
    "import os\n",
    "import numpy as np\n",
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import mahotas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 33941,
     "status": "ok",
     "timestamp": 1742519771406,
     "user": {
      "displayName": "David Morantes Duarte",
      "userId": "14011841075109377578"
     },
     "user_tz": 300
    },
    "id": "yXlZVdBzwzyX",
    "outputId": "e09fe00d-7519-4f5a-d9a5-e6bb99c13dba"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from google.colab import drive\n",
    "drive.mount(\"/content/drive\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "executionInfo": {
     "elapsed": 31,
     "status": "ok",
     "timestamp": 1742519771409,
     "user": {
      "displayName": "David Morantes Duarte",
      "userId": "14011841075109377578"
     },
     "user_tz": 300
    },
    "id": "tqZzEMimw4W4"
   },
   "outputs": [],
   "source": [
    "base_dir = \"/content/drive/MyDrive/yout/path/to/CavFish_Colombia\" #Place the full path to Dataset_CavFish_SAM here.\n",
    "input_path = f\"{base_dir}/output_folder\"\n",
    "images = [\"2016 Rio Bita\",\"2017 AndesCol\",\"2018 AndesCol\",\"2018 Caguan The Field Museum\", \"2018 Guayavero Duda\", \"2018 Manacacias Palmarito\",\n",
    "          \"2018 Peces Ituango\", \"2018 Yungillo\",\"2019 Amoya\",\"2019 Inirida\", \"2019 Rio Vaupes\", \"2022 2023 General\"] # Image folders list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 988
    },
    "executionInfo": {
     "elapsed": 43542,
     "status": "error",
     "timestamp": 1742519873647,
     "user": {
      "displayName": "David Morantes Duarte",
      "userId": "14011841075109377578"
     },
     "user_tz": 300
    },
    "id": "SQcftZU7wdX4",
    "outputId": "d5abc1cf-9a27-46f4-e137-e8232aa16449"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-6-556ff75f29f0>:110: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  df = df._append({\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-556ff75f29f0>\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m    105\u001b[0m                         plt.title(f'Image: {image_name} Area: {contour_area}, Perimeter: {contour_perimeter}, '\n\u001b[1;32m    106\u001b[0m                                   f'Hu Moments: {hu_moments}, Zernike Moments: {zernike_moments}, Radius: {radius}')\n\u001b[0;32m--> 107\u001b[0;31m                         \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    108\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    109\u001b[0m                         \u001b[0;31m# Append the computed features to the DataFrame\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mshow\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    612\u001b[0m     \"\"\"\n\u001b[1;32m    613\u001b[0m     \u001b[0m_warn_if_gui_out_of_main_thread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 614\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_get_backend_mod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    615\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    616\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib_inline/backend_inline.py\u001b[0m in \u001b[0;36mshow\u001b[0;34m(close, block)\u001b[0m\n\u001b[1;32m     88\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     89\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mfigure_manager\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mGcf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_all_fig_managers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 90\u001b[0;31m             display(\n\u001b[0m\u001b[1;32m     91\u001b[0m                 \u001b[0mfigure_manager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     92\u001b[0m                 \u001b[0mmetadata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_fetch_figure_metadata\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigure_manager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/IPython/core/display.py\u001b[0m in \u001b[0;36mdisplay\u001b[0;34m(include, exclude, metadata, transient, display_id, *objs, **kwargs)\u001b[0m\n\u001b[1;32m    318\u001b[0m             \u001b[0mpublish_display_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetadata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetadata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    319\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 320\u001b[0;31m             \u001b[0mformat_dict\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmd_dict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minclude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minclude\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexclude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mexclude\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    321\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mformat_dict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    322\u001b[0m                 \u001b[0;31m# nothing to display (e.g. _ipython_display_ took over)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36mformat\u001b[0;34m(self, obj, include, exclude)\u001b[0m\n\u001b[1;32m    178\u001b[0m             \u001b[0mmd\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    179\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 180\u001b[0;31m                 \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mformatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    181\u001b[0m             \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    182\u001b[0m                 \u001b[0;31m# FIXME: log the exception\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<decorator-gen-2>\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36mcatch_format_error\u001b[0;34m(method, self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    222\u001b[0m     \u001b[0;34m\"\"\"show traceback on failed format call\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    223\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 224\u001b[0;31m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    225\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    226\u001b[0m         \u001b[0;31m# don't warn on NotImplementedErrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    339\u001b[0m                 \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    340\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 341\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    342\u001b[0m             \u001b[0;31m# Finally look for special method names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    343\u001b[0m             \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(fig, fmt, bbox_inches, base64, **kwargs)\u001b[0m\n\u001b[1;32m    149\u001b[0m         \u001b[0mFigureCanvasBase\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    150\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 151\u001b[0;31m     \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbytes_io\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    152\u001b[0m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbytes_io\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    153\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mfmt\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'svg'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)\u001b[0m\n\u001b[1;32m   2153\u001b[0m                 \u001b[0;31m# so that we can inject the orientation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2154\u001b[0m                 \u001b[0;32mwith\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"_draw_disabled\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnullcontext\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2155\u001b[0;31m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2156\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mbbox_inches\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2157\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mbbox_inches\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"tight\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[1;32m     92\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mwraps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     93\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdraw_wrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 94\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     95\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_rasterizing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     96\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstop_rasterizing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/figure.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m   3255\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3256\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3257\u001b[0;31m                 mimage._draw_list_compositing_images(\n\u001b[0m\u001b[1;32m   3258\u001b[0m                     renderer, self, artists, self.suppressComposite)\n\u001b[1;32m   3259\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/image.py\u001b[0m in \u001b[0;36m_draw_list_compositing_images\u001b[0;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[1;32m    132\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mnot_composite\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mhas_images\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0martists\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 134\u001b[0;31m             \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    135\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    136\u001b[0m         \u001b[0;31m# Composite any adjacent images together\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m   3179\u001b[0m             \u001b[0m_draw_rasterized\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroot\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martists_rasterized\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3180\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3181\u001b[0;31m         mimage._draw_list_compositing_images(\n\u001b[0m\u001b[1;32m   3182\u001b[0m             renderer, self, artists, self.get_figure(root=True).suppressComposite)\n\u001b[1;32m   3183\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/image.py\u001b[0m in \u001b[0;36m_draw_list_compositing_images\u001b[0;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[1;32m    132\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mnot_composite\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mhas_images\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0martists\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 134\u001b[0;31m             \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    135\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    136\u001b[0m         \u001b[0;31m# Composite any adjacent images together\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/image.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m    597\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw_image\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrans\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    598\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 599\u001b[0;31m             im, l, b, trans = self.make_image(\n\u001b[0m\u001b[1;32m    600\u001b[0m                 renderer, renderer.get_image_magnification())\n\u001b[1;32m    601\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mim\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/image.py\u001b[0m in \u001b[0;36mmake_image\u001b[0;34m(self, renderer, magnification, unsampled)\u001b[0m\n\u001b[1;32m    900\u001b[0m         clip = ((self.get_clip_box() or self.axes.bbox) if self.get_clip_on()\n\u001b[1;32m    901\u001b[0m                 else self.get_figure(root=True).bbox)\n\u001b[0;32m--> 902\u001b[0;31m         return self._make_image(self._A, bbox, transformed_bbox, clip,\n\u001b[0m\u001b[1;32m    903\u001b[0m                                 magnification, unsampled=unsampled)\n\u001b[1;32m    904\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/image.py\u001b[0m in \u001b[0;36m_make_image\u001b[0;34m(self, A, in_bbox, out_bbox, clip_bbox, magnification, unsampled, round_to_pixel_border)\u001b[0m\n\u001b[1;32m    509\u001b[0m                     \u001b[0moutput_alpha\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m255\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mA\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muint8\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    510\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 511\u001b[0;31m                     output_alpha = _resample(  # resample alpha channel\n\u001b[0m\u001b[1;32m    512\u001b[0m                         self, A[..., 3], out_shape, t, alpha=alpha)\n\u001b[1;32m    513\u001b[0m                 output = _resample(  # resample rgb channels\n",
      "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/matplotlib/image.py\u001b[0m in \u001b[0;36m_resample\u001b[0;34m(image_obj, data, out_shape, transform, resample, alpha)\u001b[0m\n\u001b[1;32m    208\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mresample\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\u001b[0m         \u001b[0mresample\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimage_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_resample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 210\u001b[0;31m     _image.resample(data, out, transform,\n\u001b[0m\u001b[1;32m    211\u001b[0m                     \u001b[0m_interpd_\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0minterpolation\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    212\u001b[0m                     \u001b[0mresample\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# Function to calculate the center of mass of a mask using image moments\n",
    "def calculate_center_of_mass(mask):\n",
    "    \"\"\"\n",
    "    Calculates the center of mass of the given mask.\n",
    "\n",
    "    Args:\n",
    "        mask (np.array): Binary image mask.\n",
    "\n",
    "    Returns:\n",
    "        tuple: (cx, cy) coordinates representing the center of mass.\n",
    "    \"\"\"\n",
    "    m = cv2.moments(mask)\n",
    "    cx = int(m['m10'] / m['m00'])\n",
    "    cy = int(m['m01'] / m['m00'])\n",
    "    return (cx, cy)\n",
    "\n",
    "# Function to calculate the maximum radius from the centroid to the contour points\n",
    "def calculate_radius(centroid, contour):\n",
    "    \"\"\"\n",
    "    Calculates the maximum distance (radius) from the centroid to the points in the contour.\n",
    "\n",
    "    Args:\n",
    "        centroid (tuple): (x, y) coordinates of the centroid.\n",
    "        contour (np.array): Contour points array.\n",
    "\n",
    "    Returns:\n",
    "        float: Maximum distance from the centroid to the contour.\n",
    "    \"\"\"\n",
    "    distances = np.sqrt((contour[:, 0, 0] - centroid[0])**2 + (contour[:, 0, 1] - centroid[1])**2)\n",
    "    return np.max(distances)\n",
    "\n",
    "# Loop through each image folder specified in the list 'images'\n",
    "for image in images:\n",
    "    # Define the root directory where predictions are stored for the current image folder\n",
    "    root_directory = f\"{input_path}/{image}\"\n",
    "\n",
    "    # Create an empty DataFrame to store computed features\n",
    "    df = pd.DataFrame(columns=[\n",
    "        'Image Name', 'Area', 'Perimeter', 'Image Center', 'Center of Mass',\n",
    "        'Hu Moment 1', 'Hu Moment 2', 'Hu Moment 3', 'Hu Moment 4', 'Hu Moment 5', 'Hu Moment 6',\n",
    "        'Zernike Moment 1', 'Zernike Moment 2', 'Zernike Moment 3',\n",
    "        'ext_left', 'ext_right', 'Radius'\n",
    "    ])\n",
    "\n",
    "    # Iterate over the root directory and then each subdirectory to read every .npy file\n",
    "    for prediction_directory in os.listdir(root_directory):\n",
    "        prediction_directory = os.path.join(root_directory, prediction_directory)\n",
    "        if os.path.isdir(prediction_directory):\n",
    "            for filename in os.listdir(prediction_directory):\n",
    "                if filename.endswith('.npy'):\n",
    "                    prediction_path = os.path.join(prediction_directory, filename)\n",
    "\n",
    "                    # Load the mask from the .npy file and convert it to unsigned 8-bit integer type\n",
    "                    mask_CH = np.load(prediction_path)\n",
    "                    mask_CH = mask_CH.astype(np.uint8)\n",
    "\n",
    "                    # Apply morphological closing and opening to clean up the mask\n",
    "                    kernel = np.ones((5, 5), np.uint8)\n",
    "                    closing = cv2.morphologyEx(mask_CH, cv2.MORPH_CLOSE, kernel)\n",
    "                    mask_CH = cv2.morphologyEx(closing, cv2.MORPH_OPEN, cv2.getStructuringElement(cv2.MORPH_CROSS, (13, 13)))\n",
    "\n",
    "                    # Find contours in the processed mask\n",
    "                    contours, _ = cv2.findContours(mask_CH, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
    "\n",
    "                    if contours:\n",
    "                        contour = contours[0]\n",
    "\n",
    "                        # Calculate image moments and compute Hu Moments for shape descriptors\n",
    "                        moments = cv2.moments(contour)\n",
    "                        hu_moments = cv2.HuMoments(moments).flatten()\n",
    "\n",
    "                        # Calculate the center of mass from the mask\n",
    "                        center_of_mass = calculate_center_of_mass(mask_CH)\n",
    "\n",
    "                        # Calculate the contour area and perimeter\n",
    "                        contour_area = cv2.contourArea(contour)\n",
    "                        contour_perimeter = cv2.arcLength(contour, True)\n",
    "\n",
    "                        # Calculate the maximum radius from the center of mass to the contour\n",
    "                        radius = calculate_radius(center_of_mass, contour)\n",
    "\n",
    "                        # Calculate Zernike moments using mahotas with the calculated radius\n",
    "                        zernike_moments = mahotas.features.zernike_moments(mask_CH, radius=radius)\n",
    "\n",
    "                        # Determine the center of the image\n",
    "                        height, width = mask_CH.shape\n",
    "                        image_center = (width // 2, height // 2)\n",
    "\n",
    "                        # Find the extreme left and right points of the contour\n",
    "                        ext_left = tuple(contour[contour[:, :, 0].argmin()][0])\n",
    "                        ext_right = tuple(contour[contour[:, :, 0].argmax()][0])\n",
    "\n",
    "                        # Convert the mask to color for visualization and draw contours and key points\n",
    "                        mask_CH_color = cv2.cvtColor(mask_CH, cv2.COLOR_GRAY2BGR)\n",
    "                        cv2.drawContours(mask_CH_color, [contour], -1, (0, 255, 0), 2)\n",
    "                        cv2.circle(mask_CH_color, image_center, 5, (0, 0, 255), -1)  # Red for image center\n",
    "                        cv2.circle(mask_CH_color, center_of_mass, 5, (0, 255, 255), -1)  # Yellow for center of mass\n",
    "                        cv2.circle(mask_CH_color, ext_left, 5, (0, 0, 255), -1)\n",
    "                        cv2.circle(mask_CH_color, ext_right, 5, (0, 0, 255), -1)\n",
    "                        image_name = filename.split('_')[0]\n",
    "\n",
    "                        # Display the original mask with contours, image center, center of mass, and extreme points overlay\n",
    "                        plt.imshow(mask_CH, cmap='gray')\n",
    "                        plt.imshow(mask_CH_color, alpha=0.6)\n",
    "                        plt.title(f'Image: {image_name} Area: {contour_area}, Perimeter: {contour_perimeter}, '\n",
    "                                  f'Hu Moments: {hu_moments}, Zernike Moments: {zernike_moments}, Radius: {radius}')\n",
    "                        plt.show()\n",
    "\n",
    "                        # Append the computed features to the DataFrame\n",
    "                        df = df._append({\n",
    "                            'Image Name': image_name, 'Area': contour_area, 'Perimeter': contour_perimeter,\n",
    "                            'Image Center': image_center, 'Center of Mass': center_of_mass,\n",
    "                            'Hu Moment 1': hu_moments[0], 'Hu Moment 2': hu_moments[1],\n",
    "                            'Hu Moment 3': hu_moments[2], 'Hu Moment 4': hu_moments[3], 'Hu Moment 5': hu_moments[4],\n",
    "                            'Hu Moment 6': hu_moments[5], 'Zernike Moment 1': zernike_moments[0],\n",
    "                            'Zernike Moment 2': zernike_moments[1], 'Zernike Moment 3': zernike_moments[2],\n",
    "                            'ext_left': ext_left, 'ext_right': ext_right, 'Radius': radius\n",
    "                        }, ignore_index=True)\n",
    "\n",
    "    # Save the DataFrame with the computed features as a CSV file\n",
    "    df.to_csv(f'{root_directory}/{image}_features.csv', index=False)"
   ]
  }
 ],
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